MilaNLProc/survey-language-technologies huggingface dataset:
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed full time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Homemaker
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Watch sports;Listen to hiphop and rap 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Rarely
LLMs used: None of these 
LLM use cases: Other (specify) only when contacting companies on a chat
Comments: no
Gender: Male 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Prefer not to say 
Education: Undergraduate degree
Mother's education: Prefer not to say
Father's education: Prefer not to say
Self-assessed socioeconomic status (1-10): 6
Home: Rent 
Employment: Employed full time
Occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Mother's occupation: Prefer not to say
Father's occupation: Prefer not to say
Hobbies: Listen to rock/indie music;Go to gigs;Exercise;Attend football matches;Watch sports 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Rarely
LLMs used: None of these 
LLM use cases: Writing (e.g., composing emails);Solving math or logical problems;Play games;Answering questions about general knowledge 
Contexts of LLM use: Work;Learning;Technical 
Prompt 1: where is the nearest airport
Prompt 2: what weather front is coming in
Prompt 3: what time is the event
Prompt 4: how long is does it take to get to london
Prompt 5: how much is the ferrari
Prompt 6: what is the full capacity at wembley stadium
Prompt 7: how much is the laptop
Prompt 8: turn on  magic radio 
Prompt 9: find the nearest toilet
Prompt 10: how far is it to the moon
Comments: great survey
Gender: Female 
Age: 18-24
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 3
Home: Other (Please specify) Living with parents
Employment: Employed part time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Use social media;Exercise 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Coding;Translation;Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Generic chatbot conversation;Play games;Completing assignments 
Contexts of LLM use: Work 
Prompt 1: Can you spell check this text for me its for my work write up?
Prompt 2: Can you make Georgia doing the dishwasher
Prompt 3: can you make cozy into a carpenter
Prompt 4: What does a carpenter do?
Gender: Male 
Age: 18-24
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Other (Please Specify) Partnered
First language: English 
Religion: Jewish 
Education: High school or below
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 4
Home: Prefer not to say 
Employment: Not employed, but looking for work
Occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to rock/indie music;Use social media;Other (Please specify) Astrophotography/Gardening
Devices used daily: Laptop;Smartphone 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Every day
LLMs used: ChatGPT 
LLM use cases: Brainstorming 
Contexts of LLM use: Learning;Technical 
Prompt 1: Hello! chat gpt can you help me garden
Prompt 2: ow much terps should i add to 1.2 grams for 4% terps
Prompt 3: what would 1ml be 
Prompt 4: should i vacuum seal my jar for decarbing? isnt there already air in the jar
Prompt 5: hats the max dose of cannabis? how much can you brain handle till it cant process it
Prompt 6: no like whats the limit. max limit not overwhelming just max
Prompt 7: Smoking through my nose when im sic
Prompt 8: yeah but my throat is sore thats why i went for the nose
Gender: Female 
Age: 18-24
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Own 
Employment: Not employed, unable to work due to a disability or illness
Occupation: Prefer not to say
Mother's occupation: Prefer not to say
Father's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Hobbies: Go to gigs;Use social media;Go to museums and galleries 
Devices used daily: Smartphone;Laptop;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Translation;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge;Generic chatbot conversation;Paraphrasing or finding synonyms;Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Summarizing long texts 
Contexts of LLM use: Personal;Learning 
Prompt 1: What is anhedonia?
Prompt 2: How can you heal anhedonia?
Prompt 3: Is it possible to heal emotional numbness?
Prompt 4: Can depression affect your concentration?
Prompt 5: Why can’t I concentrate on anything anymore?
Prompt 6: Can you tell me more about the inca empire?
Prompt 7: How to sign up for personal independence payment?
Prompt 8: What is the best type of therapy for autistic people
Prompt 9: How to potty train a puppy
Prompt 10: My puppy won’t go toilet outside what do I do
Gender: Male 
Age: 25-34
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Employed full time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Listen to rock/indie music;Go to gigs;Use social media 
Devices used daily: Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Other (specify) I wouldn't find any of them useful
Frequency of LLM use: Never
Gender: Female 
Age: 18-24
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Not employed, unable to work due to a disability or illness
Occupation: Prefer not to say
Mother's occupation: Homemaker
Father's occupation: Homemaker
Hobbies: Use social media;Do arts and crafts 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Rarely
LLMs used: Character.AI;ChatGPT 
LLM use cases: Writing (e.g., composing emails);Generic chatbot conversation 
Contexts of LLM use: Creative or artistic 
Prompt 1: can you ask more questions about seungmin's overall relationship with himself in the second half of the story?
Prompt 2: can you ask more questions about seungmin's overall relationship with minho in the second half of the story?
Prompt 3: can you ask more questions about seungmin's overall relationship with chan in the second half of the story?
Prompt 4: can you ask more questions about seungmin's overall relationship with changbin in the second half of the story?
Prompt 5: can you ask more questions about seungmin's overall relationship with hyunjin in the second half of the story?
Prompt 6: can you ask more questions about seungmin's overall relationship with jisung in the second half of the story?
Prompt 7: can you ask more questions about seungmin's overall relationship with felix in the second half of the story?
Prompt 8: can you ask more questions about seungmin's overall relationship with jeongin in the second half of the story?
Gender: Female 
Age: 60+
Nationality: United States
Marital status: Divorced 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Employed full time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Go to gigs;Exercise;Use social media;Listen to hiphop and rap;Watch dance or ballet 
Devices used daily: Laptop;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Text-to-Speech (i.e, computers being able to read out loud written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Paraphrasing or finding synonyms;Generic chatbot conversation 
Contexts of LLM use: Work 
Prompt 1: How do I lower my car insurance 
Prompt 2: Please rewrite the following paragraph 
Prompt 3: In the paragraph you just wrote, replace then name Ann with Bruce
Prompt 4: Rewrite this sentence in a more technical sounding  manner
Prompt 5: What are some examples of work discrimination 
Prompt 6: What can I do about discrimination at work
Prompt 7: What jobs are good for people over 55
Comments: No
Gender: Female 
Age: 25-34
Nationality: United Kingdom
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Other, please specify. Spiritual
Education: Prefer not to say
Mother's education: Undergraduate degree
Father's education: Prefer not to say
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Not employed and not looking for work
Occupation: Homemaker
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Hobbies: Use social media 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Paraphrasing or finding synonyms;Generic chatbot conversation;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Personal;Entertainment;Creative or artistic 
Prompt 1: Create a shopping list for a single woman in London
Prompt 2: Why does water appear blue in large quantities?
Prompt 3: List the Marvel films in chronological order
Prompt 4: What was the first film ever made?
Prompt 5: What is the history of hapsberg jaw?
Prompt 6: Which species can cross breed?
Prompt 7: Are there any living human clones?
Prompt 8: Write a business plan for a commercial property company
Prompt 9: What country never has night time?
Prompt 10: Can you see an itch under a microscope?
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Divorced 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed full time
Occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Mother's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Father's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Hobbies: Listen to classical music;Visit to stately homes 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Rarely
LLMs used: Google Gemini 
LLM use cases: Generic chatbot conversation;Answering questions about general knowledge 
Contexts of LLM use: Personal 
Prompt 1: top kdramas
Prompt 2: best cdramas
Gender: Male 
Age: 18-24
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Student
Occupation: Prefer not to say
Mother's occupation: Homemaker
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Exercise;Use social media;Watch sports 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Paraphrasing or finding synonyms 
Contexts of LLM use: Entertainment;School/University;Learning;Personal 
Prompt 1: does arrest simply mean that they were apprehended but not sentenced?
Prompt 2: Can you help me formulate a question for an essay
Prompt 3: what does this mean?  "Both sides, however, were hampered by a view that equated criminality with immorality"
Prompt 4: to what extent was the renaissance influential in shaping modern art?
Prompt 5: does mass media undermine democracy?
Gender: Male 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Hobbies: Watch sports;Attend football matches;Exercise;Go to museums and galleries 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Microsoft Bing AI 
LLM use cases: Generic chatbot conversation;Writing (e.g., composing emails);Analyze data;Learning (e.g., explaining complex concepts in simple terms);Collecting references 
Contexts of LLM use: Work;Personal;Learning;Technical 
Prompt 1: Parking in Sheffield
Prompt 2: Sheffield tram lines
Prompt 3: Marianne Faithful 
Prompt 4: Easter dates 2025
Prompt 5: Days since 17th June 1991
Prompt 6: Royal Meteorological Society phone number
Prompt 7: Best regular saver bank accounts
Prompt 8: Florida park tickets offers
Prompt 9: Cat sanctuary suppliers
Prompt 10: Barclays banking issues
Comments: I am a little nervous of AI technology but don’t always recognise applications and tasks that I am undertaking where AI is operating .
Interesting survey best wishes with the study
Gender: Female 
Age: 60+
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Own 
Employment: Employed full time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Do arts and crafts 
Devices used daily: Laptop;Smartphone 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Never
Gender: Non-binary 
Age: 35-44
Nationality: United States
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed part time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Homemaker
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to jazz;Listen to hiphop and rap;Use social media;Go to museums and galleries;Do arts and crafts 
Devices used daily: Smartphone;Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Text-to-Speech (i.e, computers being able to read out loud written language);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Sometimes
LLMs used: Other Meta
LLM use cases: Writing (e.g., composing emails);Brainstorming;Translation;Paraphrasing or finding synonyms;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Generic chatbot conversation;Digital content creation (e.g., creation of social media content);Play games;Completing assignments;Learning (e.g., explaining complex concepts in simple terms);Get information about current events;Answering questions about general knowledge 
Contexts of LLM use: Work;School/University;Personal;Learning;Creative or artistic;Entertainment 
Prompt 1: How do I establish boundaries?
Prompt 2: What resources are available for someone that's houseless.
Prompt 3: Tell me something funny.
Prompt 4: How do I find food?
Gender: Female 
Age: 35-44
Nationality: United Kingdom
Ethnicity: Hispanic 
Marital status: Single 
First language: English   
Religion: Prefer not to say 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer);Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to classical music 
Devices used daily: Laptop;Smartwatch;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes) 
Frequency of LLM use: Every day
LLMs used: Google Gemini 
LLM use cases: Translation 
Contexts of LLM use: Entertainment 
Prompt 1: entertainment
Prompt 2: translation
Prompt 3: writing
Prompt 4: proofreading
Prompt 5: learning
Prompt 6: work
Prompt 7: social
Prompt 8: love
Prompt 9: sport
Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: Prefer not to say
Father's education: Prefer not to say
Self-assessed socioeconomic status (1-10): 7
Home: Other (Please specify) Live with my parents
Employment: Employed part time
Occupation: Prefer not to say
Mother's occupation: Prefer not to say
Father's occupation: Prefer not to say
Hobbies: Listen to rock/indie music;Listen to hiphop and rap;Use social media 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Text-to-Speech (i.e, computers being able to read out loud written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
Frequency of LLM use: Sometimes
LLMs used: Google Gemini 
LLM use cases: Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge 
Contexts of LLM use: Learning;Personal
Gender: Female 
Age: 55-60
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 8
Home: Own 
Employment: Employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Hobbies: Visit to stately homes;Use social media;Exercise 
Devices used daily: Smartphone;Tablet;Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Rarely
Comments: I do t use them
Gender: Male 
Age: 45-54
Nationality: United States
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Employed full time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Homemaker
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Google Gemini 
Prompt 1: tell me the weather 
Prompt 2: set and alarm 
Prompt 3: what dose X mean 
Prompt 4: Define X for me 
Prompt 5: write an example of X for me
Gender: Male 
Age: 25-34
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Go to gigs;Listen to rock/indie music;Attend football matches;Watch sports;Exercise;Go to museums and galleries 
Devices used daily: Laptop;Smartphone 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Rarely
LLMs used: Microsoft Bing AI;Google Gemini 
LLM use cases: Play games;Answering questions about general knowledge 
Contexts of LLM use: Personal 
Prompt 1: who is the best tennis player
Prompt 2: how to sharpen up my cv
Prompt 3: tell me about life
Prompt 4: what was the weather in missoula montance in July 1989
Prompt 5: who is your favorite twin peaks character
Prompt 6: who is the favourite to win this year's champions league
Prompt 7: do you ever get bored
Prompt 8: can you give me 5 tips on how to stay calm
Prompt 9: do you like coffee and a piece of cherry pie?
Prompt 10: how many films did david lynch make?
Comments: no
Gender: Male 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Rent 
Employment: Employed full time
Occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Mother's occupation: Homemaker
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Listen to rock/indie music;Exercise;Use social media;Watch sports 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Grok 
LLM use cases: Writing (e.g., composing emails);Brainstorming;Get information about current events;Answering questions about general knowledge 
Contexts of LLM use: Work;Personal
Gender: Female 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: Graduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Own 
Employment: Employed part time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Go to gigs;Use social media 
Devices used daily: Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Never
Gender: Female 
Age: 25-34
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Not employed, unable to work due to a disability or illness
Occupation: Homemaker
Mother's occupation: Homemaker
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Other (Please specify) gaming
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Rarely